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Background/Objectives: Type 1 diabetes (T1D) and multiple sclerosis (MS) are autoimmune, multifactorial, organ-specific disorders mediated by immune cells. Their co-occurrence has been partially attributed to shared genetics and environmental factors. We aimed to dissect the shared genetic architecture between T1D and MS using large-scale genome-wide association studies (GWASs) and colocalization analyses. Methods: We applied a Bayesian colocalization framework to two large-scale GWAS data sets: a T1D study comprising 18,942 cases and 501,638 controls, and an MS GWAS including 14,802 cases and 26,703 controls. Results: We identified 26 shared colocalizing association signals between T1D and MS. Among them, seven loci (EOMES, RGS14, DLL1, ZNF438/ZEB1, SESN3, WARS1/SLC25A47, and IRF8) were novel for T1D and two (UBAC2 and LAT) for MS. Several signals showed supportive evidence in additional datasets and demonstrated functional annotation characteristics consistent with disease involvement. Conclusions: Colocalization can be a powerful discovery tool for disorders with co-divided genetic architecture, as prioritizing shared rather than individual causal variants may enhance the detection of novel loci. Our findings indicate that T1D and MS predominantly share general autoimmune susceptibility signals (17/26), rather than disease-specific (private), often with opposite direction of effect (9/26), underscoring their immunological heterogeneity.